| China’s daily urban solid waste production is increasing with the growth of urbanization,and the treatment of urban solid waste has become an important issue not only in China,but also around the world.Because municipal solid waste is very complicated and has very distinct properties,complex biochemical degradation reactions will occur after landfill is finished,and the leachate and landfill gas created during the degradation process can easily lead to leachate leakage,pollute the environment,landfill explosion,and other hazards.The type of pore water and the impact of hydraulic permeability features on the leachate’s migration process inside the reactor are crucial factors to consider while researching water transport in landfills.Gas permeation properties of landfill trash are a key factor in landfill gas pollution control and recycling engineering because they have a significant impact on the process of landfill gas migration.The strength parameters of municipal solid waste change with the biochemical degradation process,leading to settlement deformation,landfill instability,and other engineering issues.These parameters are important for settlement prediction and landfill capacity assessment of built landfills.The corrected main compression index,modified secondary compression index,and strength parameters of municipal solid waste.To properly assess the landfill and plan the fill,it is crucial to research the selection of pertinent parameters.Under the funding of the National Natural Science Foundation of China(52008071)and Dalian Science and Technology Innovation Fund(2022JJ2GX031),this thesis carries out the research on the relationship between engineering parameters and influencing factors,analyzes the relevant factors affecting the permeability characteristics,compression characteristics and strength characteristics of landfills,and gives the recommended function range of relevant factors and parameters,and proposes the urban domestic waste engineering characteristics parameter prediction model considering the influence of skeleton strength on the basis of Duncan-Zhang model.Based on the Duncan-Zhang model,a model of urban domestic waste settlement deformation considering the influence of skeleton strength is proposed,and a prediction model of urban domestic waste engineering parameters based on RBF neural network is established and a prediction software of urban domestic waste engineering parameters is developed,which provides a theoretical basis and analysis tools for the selection of waste engineering parameters in landfill design and operation.The main research contents and results of this thesis are as follows:(1)The distribution rules of waste engineering parameters with different food waste contents were compared,and the effects of burial depth,porosity,degradation,composition,volumetric moisture content,dry weight and waste unit weight on waste infiltration characteristics,compression characteristics and strength characteristics were analyzed,and the linear relationship between single influencing factor and parameters,two-dimensional relationship between multiple influencing factors and parameters and three-dimensional relationship were analyzed,and the corresponding function values and the distribution ranges of the corresponding model parameters were given and the methods of taking values.(2)Based on the Duncan-Zhang model,a settlement deformation model for MSW considering the effect of skeleton degradation is proposed.The model parameters are determined based on the results of the triaxial solidification and drainage tests,and the effects of the initial pore ratio,fiber component content and degradable component content on the model parameters are analyzed,and the recommended parameter ranges are given for different food waste components.The influence of the initial pore ratio,the content of degradable fraction,the content of fiber fraction and other factors on the settling of waste was also analyzed.(3)Based on the recommended range of functions proposed in the infiltration,compression,and strength characteristics,RBF neural network,BP neural network,and SVR support vector machine regression were used to predict the infiltration coefficient,compression index,and strength parameters,and the prediction results showed that the prediction accuracy and performance evaluation indexes of the RBF neural network prediction model were better than those of Other prediction methods.The influence of inputting different parameters on the prediction results was analyzed,and the more influencing factors,the higher the prediction accuracy.Combined with the prediction results,in the permeability characteristics,the best prediction effect was obtained by inputting porosity,age and initial degradable component;inputting dry weight,component and volumetric water content as input parameter pairs,the best prediction effect was obtained for the garbage modified primary compression index,and in the prediction of modified secondary compression index,the best prediction effect was obtained by inputting initial porosity ratio,In predicting the modified sub-compression index,the best prediction effect was obtained by inputting the initial pore ratio,compressible component and age;in predicting the strength parameters,the best prediction effect was obtained by inputting the axial strain,initial pore ratio and age.(4)Based on MATLAB APP DESIGNER toolbox,we developed the Prediction Parameter of Municipal Domestic Waste Engineering Characteristics software(PPMSW V1.0),which can predict the waste engineering characteristics parameters and give the comparison with the corresponding parameters in the database by selecting different initial parameters for input according to the actual site conditions.The software can be used for the selection of relevant parameters in the initial design stage of the project,and provide theoretical basis for the development of landfill operation and related engineering control measures. |
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